Search

Double-stranded RNA (dsRNA) is produced during most viral infections, and immunohistochemical detection of dsRNA has been proposed as a potential screening marker for viral replication. The anti-dsRNA monoclonal antibody clone 9D5 is more sensitive than the established clone J2 but has not been validated in formalin-fixed paraffin-embedded (FFPE) tissue. This study aimed to test and compare the performance of the anti-dsRNA monoclonal antibodies, 9D5 and J2, in FFPE tissue using an automated staining platform. Archived clinical tissue samples with viral infections (n = 34) and uninfected controls (n = 30) were examined. Immunohistochemical staining for dsRNA (9D5 and J2) and virus-specific epitopes was performed. 9D5 provided a similar staining pattern but a higher signal-to-noise ratio than J2. The following proportions of virus-infected tissue samples were dsRNA-positive: SARS-CoV-2 (5/5), HPV (6/6), MCV (5/5), CMV (5/6), HSV (4/6), and EBV (0/6). Also, 18 of 30 uninfected samples were dsRNA positive, and an association between fixation time and intensity was observed. However, signals in all samples were markedly reduced by pretreatment with dsRNA-specific RNAse-III, indicating a specific reaction. In conclusion, dsRNA can be demonstrated in most viral infections with immunohistochemistry in FFPE tissue but with low clinical specificity. The antibody clone 9D5 performs better than clone J2. Double-stranded RNA (dsRNA) is produced during most viral infections, and immunohistochemical detection of dsRNA has been proposed as a potential screening marker for viral replication. The anti-dsRNA monoclonal antibody clone 9D5 is more sensitive than the established clone J2 but has not been validated in formalin-fixed paraffin-embedded (FFPE) tissue. This study aimed to test and compare the performance of the anti-dsRNA monoclonal antibodies, 9D5 and J2, in FFPE tissue using an automated staining platform. Archived clinical tissue samples with viral infections (n = 34) and uninfected controls (n = 30) were examined. Immunohistochemical staining for dsRNA (9D5 and J2) and virus-specific epitopes was performed. 9D5 provided a similar staining pattern but a higher signal-to-noise ratio than J2. The following proportions of virus-infected tissue samples were dsRNA-positive: SARS-CoV-2 (5/5), HPV (6/6), MCV (5/5), CMV (5/6), HSV (4/6), and EBV (0/6). Also, 18 of 30 uninfected samples were dsRNA positive, and an association between fixation time and intensity was observed. However, signals in all samples were markedly reduced by pretreatment with dsRNA-specific RNAse-III, indicating a specific reaction. In conclusion, dsRNA can be demonstrated in most viral infections with immunohistochemistry in FFPE tissue but with low clinical specificity. The antibody clone 9D5 performs better than clone J2.

Immunohistochemistry (IHC) has for decades been an integrated method within pathology applied to gain diagnostic, prognostic, and predictive information. However, the multimodality of the analytical phase of IHC is a challenge to ensure the reproducibility of IHC, which has been documented by external quality assessment (EQA) programs for many biomarkers. More than 600 laboratories participate in the Nordic immunohistochemical Quality Control EQA program for IHC. In the period, 2017-2021, 65 different biomarkers were assessed and a total of 31,967 results were evaluated. An overall pass rate of 79% was obtained being an improvement compared with 71% for the period, 2003-2015. The pass rates for established predictive biomarkers (estrogen receptor, progesterone receptor, and HER2) for breast carcinoma were most successful showing mean pass rates of 89% to 92%. Diagnostic IHC biomarkers as PAX8, SOX10, and different cytokeratins showed a wide spectrum of pass rates ranging from 37% to 95%, mean level of 75%, and attributed to central parameters as access to sensitive and specific antibodies but also related to purpose of the IHC test and validation performed accordingly to this. Seven new diagnostic biomarkers were introduced, and all showed inferior pass rates compared with the average level for diagnostic biomarkers emphasizing the challenge to optimize, validate, and implement new IHC biomarkers. Nordic immunohistochemical Quality Control operates by "Fit-For-Purpose" EQA principles and for programmed death-ligand 1, 2 segments are offered aligned to the "3-dimensional" approach-bridging diagnostic tests, drugs to be offered, and diseases addressed. Mean pass rates of 65% and 79% was obtained in the 2 segments for programmed death-ligand 1.

This paper is number 8 in a series developed through a partnership between ISIMM and NordiQC with the purpose of reporting research assessing the performance characteristics of immunoassays in an external proficiency testing program.

Immunohistochemistry for Uroplakin (UP) II and III is used to determine urothelial origin of carcinomas of unknown primary site and are especially valuable to differentiate urothelial carcinomas (UCs) from lung squamous cell carcinomas and prostate carcinomas. In the Nordic immunohistochemical Quality Control assessment scheme, only 45% of the participants obtained a sufficient staining result for UP. Primary antibodies (Abs) against UPII were most successful with a pass rate of 86%. No Abs against UPIII provided sufficient staining results. A comparative study was carried out on a larger cohort of tissue samples with optimized methods for the UPII mouse monoclonal antibody (mmAb) clone BC21, UPIII mmAb clone AU-1, and rabbit monoclonal antibody (rmAb) clone SP73 to evaluate the performance in a standardized way. Tissue microarrays containing 58 UCs, 111 non-UCs, and 20 normal tissues were included. The UP stains were evaluated by using H-score. Based on H-scores, samples were categorized as high-expressor (150 to 300), moderate-expressor (10 to 149), low-expressor (1 to 9), and negative (150 for the UPII Ab. The 2 UPIII Abs gave an analytical specificity of 100% compared with 97% for the UPII Ab being positive in 2 ovarian carcinomas and 1 cervical squamous cell carcinoma.

This paper is number 6 in a series developed through a partnership between ISIMM and Nordic IHC Quality Control with the purpose of reporting research assessing the performance characteristics of immunoassays in an external proficiency testing program.

Survival of diffuse large B-cell lymphoma (DLBCL) patients has improved by inclusion of rituximab. Refractory/recurrent disease caused by treatment resistance is, however, a major problem. Determinants of rituximab sensitivity are not fully understood, but effect of rituximab are enhanced by antagonizing cell surface receptor CXCR4. In a two-step strategy, we tested the hypothesis that prognostic value of CXCR4 in DLBCL relates to rituximab treatment, due to a hampering effect of CXCR4 on the response of DLBCL cells to rituximab. First, by investigating the prognostic impact of CXCR4 mRNA expression separately for CHOP (n=181) and R-CHOP (n=233) cohorts and, second, by assessing the interaction between CXCR4 and rituximab in DLBCL cell lines. High CXCR4 expression level was significantly associated with poor outcome only for R-CHOP-treated patients, independent of IPI score, CD20 expression, ABC/ GCB and B-cell-associated gene signature (BAGS) classifications. s. For responsive cell lines, inverse correlation was observed between rituximab sensitivity and CXCR4 surface expression, rituximab induced upregulation of surface-expressed CXCR4, and growth-inhibitory effect of rituximab increased by plerixafor, supporting negative impact of CXCR4 on rituximab function. In conclusion, CXCR4 is a promising independent prognostic marker for R-CHOP-treated DLBCL patients, possibly due to inverse correlation between CXCR4 expression and rituximab sensitivity.

Immunohistochemical staining for Ki-67 is used to calculate a Ki-67 proliferation index (PI) that carries prognostic and predictive information in various cancers including breast carcinomas. Studies have documented challenges for observers to reproducibly estimate the Ki-67 PI. At present, no international consensus exists concerning scoring method (eg, hotspots vs. overall average, digital vs. manual counting) or even the definition of a Ki-67-positive cell. To clarify the approach to Ki-67 scoring and evaluation of the interobserver agreement among participants in the Nordic Immunohistochemical Quality Control (NordiQC) Breast Cancer Module, a study was set up on the basis of an online web module containing 15 digitized tissue microarray cores of breast carcinomas stained for Ki-67 in the NordiQC reference laboratory. All participants were invited to attend the study. In addition to Ki-67 scoring, they were asked to disclose their preferred method for Ki-67 estimation and their job title. For comparison, slides were analyzed using a Digital Image Analysis algorithm based on Virtual Double Staining. In total, 199 participants enrolled for the study. Overall, there was a good correlation in Ki-67 PIs among the participants, although results for some cores varied significantly. However, when applying a cutoff of 20%, a relatively low κ value of 0.52 was observed. Participants scoring in hotspots reported higher Ki-67 PIs than participants estimating an overall average, and, not surprisingly, participants who considered weak Ki-67 nuclear staining positive obtained higher Ki-67 PIs than those who did not. Ki-67 PI was not correlated to job title. The Virtual Double Staining algorithm obtained Ki-67 values close to the mean value of the human observers. Our study underlines the need for international standardization and guidelines in estimation of Ki-67 PI. Digital Image Analysis may be a useful tool in this process.

This paper is number 7 in a series developed through a partnership between ISIMM and NordiQC with the purpose of reporting research assessing the performance characteristics of immunoassays in an external proficiency testing program.

Nordic Immunohistochemical Quality Control (NordiQC) performs proficiency testing for about 600 pathology laboratories in more than 50 countries. All general results are published on http://www.nordiqc.org. Over-all, about 30% of the staining results on circulated slides from tissue micro arrays have been assessed as insufficient for diagnostic use by an expert group. This paper describes the results from the two latest NordiQC runs for CD31. Out of 476 stains submitted, 30.5% were considered insufficient, mostly due to too weak or false negative staining reactions. The best results were obtained by use of mouse monoclonal antibody JC70A with an optimized protocol based on efficient heat induced epitope retrieval and a three-step polymer/multimer conjugate as visualization system. The mouse monoclonal antibody 1A10 gave unsatisfactory results in almost all cases.

Different clones, protocol conditions, instruments, and scoring/readout methods may pose challenges in introducing different PD-L1 assays for immunotherapy. The diagnostic accuracy of using different PD-L1 assays interchangeably for various purposes is unknown. The primary objective of this meta-analysis was to address PD-L1 assay interchangeability based on assay diagnostic accuracy for established clinical uses/purposes. A systematic search of the MEDLINE database using PubMed platform was conducted using "PD-L1" as a search term for 01/01/2015 to 31/08/2018, with limitations "English" and "human". 2,515 abstracts were reviewed to select for original contributions only. 57 studies on comparison of two or more PD-L1 assays were fully reviewed. 22 publications were selected for meta-analysis. Additional data were requested from authors of 20/22 studies in order to enable the meta-analysis. Modified GRADE and QUADAS-2 criteria were used for grading published evidence and designing data abstraction templates for extraction by reviewers. PRISMA was used to guide reporting of systematic review and meta-analysis and STARD 2015 for reporting diagnostic accuracy study. CLSI EP12-A2 was used to guide test comparisons. Data were pooled using random-effects model. The main outcome measure was diagnostic accuracy of various PD-L1 assays. The 22 included studies provided 376 2×2 contingency tables for analyses. Results of our study suggest that, when the testing laboratory is not able to use an Food and Drug Administration-approved companion diagnostic(s) for PD-L1 assessment for its specific clinical purpose(s), it is better to develop a properly validated laboratory developed test for the same purpose(s) as the original PD-L1 Food and Drug Administration-approved immunohistochemistry companion diagnostic, than to replace the original PD-L1 Food and Drug Administration-approved immunohistochemistry companion diagnostic with a another PD-L1 Food and Drug Administration-approved companion diagnostic that was developed for a different purpose.

Breast cancer is the most frequent cancer among women worldwide. Ki67 can be used as an immunohistochemical pseudo marker for cell proliferation to determine how aggressive the cancer is and thereby the treatment of the patient. No standard Ki67 staining protocol exists, resulting in inter-laboratory stain variability. Therefore, it is important to determine the quality control of a staining protocol to ensure correct diagnosis and treatment of patients. Currently, quality control is performed by the organization NordiQC that use an expert panel-based qualitative assessment system. However, no objective method exists to determine the quality of a staining protocol. In this study, we propose an algorithm, to objectively assess staining quality from segmented cell nuclei structures extracted from cell lines. The cell nuclei were classified into either Ki67 positive or negative to determine the Ki67 proliferation index within the cell lines. A Ki67 stain quality model based on ordinal logistic regression was developed to determine the quality of a staining protocol from features extracted from the segmented cell nuclei in the cell lines. The algorithm was able to segment and classify Ki67 positive cell nuclei with a sensitivity and positive predictive value (PPV) of 0.90 and 0.94 and Ki67 negative cell nuclei with a sensitivity and PPV of 0.78 and 0.78. The mean difference between a manual and automatic Ki67 proliferation index was -0.003 with a standard deviation of 0.056. The ordinal logistic regression model found that the stain intensity for both the Ki67 positive and Ki67 negative cell nuclei were statistically significant as parameters determining the stain quality from the cell line cores. The framework shows great promise for using cell nuclei information from cell lines to predict the staining quality of staining protocols. © 2018 International Society for Advancement of Cytometry.

Currently, diagnosis of colon cancer is based on manual examination of histopathological images by a pathologist. This can be time consuming and interpretation of the images is subject to inter- and intra-observer variability. This may be improved by introducing a computer-aided diagnosis (CAD) system for automatic detection of cancer tissue within whole slide hematoxylin and eosin (H&E) stains. Cancer disrupts the normal control mechanisms of cell proliferation and differentiation, affecting the structure and appearance of the cells. Therefore, extracting features from segmented cell nuclei structures may provide useful information to detect cancer tissue. A framework for automatic classification of regions of interest (ROI) containing either benign or cancerous colon tissue extracted from whole slide H&E stained images using cell nuclei features was proposed. A total of 1,596 ROI's were extracted from 87 whole slide H&E stains (44 benign and 43 cancer). A cell nuclei segmentation algorithm consisting of color deconvolution, k-means clustering, local adaptive thresholding, and cell separation was performed within the ROI's to extract cell nuclei features. From the segmented cell nuclei structures a total of 750 texture and intensity-based features were extracted for classification of the ROI's. The nine most discriminative cell nuclei features were used in a random forest classifier to determine if the ROI's contained benign or cancer tissue. The ROI classification obtained an area under the curve (AUC) of 0.96, sensitivity of 0.88, specificity of 0.92, and accuracy of 0.91 using an optimized threshold. The developed framework showed promising results in using cell nuclei features to classify ROIs into containing benign or cancer tissue in H&E stained tissue samples. © 2017 International Society for Advancement of Cytometry.

Immunohistochemistry Ki-67 stain is widely used for visualizing cell proliferation. The common method for scoring the proliferation is to manually select and score a hot spot. This method is time-consuming and will often not give reproducible results due to subjective selection of the hotspots and subjective scoring. An automatic hotspot detection and proliferative index scoring would be time-saving, make the determination of the Ki-67 score easier and minimize the uncertainty of the score by introducing a more objective and standardized score. Tissue Micro Array cores stained for Ki-67 and their neighbor slide stained for Pan Cytokeratin were aligned and Ki-67 positive and negative nuclei were identified inside tumor regions. A heatmap was calculated based on these and illustrates the distribution of the heterogenous response of Ki-67 positive nuclei in the tumor tissue. An automatic hot spot detection was developed and the Ki-67 score was calculated. All scores were compared with scores provided by a pathologist using linear regression models. No significant difference was found between the Ki-67 scores guided by the developed heatmap and the scores provided by a pathologist. For comparison, scores were also calculated at a random place outside the hot spot and these scores were found to be significantly different from the pathologist scores. A heatmap visualizing the heterogeneity in tumor tissue expressed by Ki-67 was developed and used for an automatic identification of hot spots in which a Ki-67 score was calculated. The Ki-67 scores did not differ significantly from scores provided by a pathologist. © 2017 International Society for Advancement of Cytometry.

Ki67 is a nuclear protein expressed during the active phases of the cell cycle, which makes it a biomarker of cell proliferation. In clinical pathology settings, immunohistochemical (IHC) detection of Ki67 is used to calculate Ki67 proliferation indices (PIs), which have prognostic information and are used to subdivide breast carcinomas and neuroendocrine neoplasias. Calculation of Ki67 PIs is notoriously hard and prone to intraobserver and interobserver variance. In addition, IHC protocol settings [such as primary antibody (Ab) clone, clone format, and stainer platform] can affect the result of the IHC assays and in turn the Ki67 PI. Digital image analysis has been suggested as a useful tool to standardize Ki67 counting. Recently, virtual double staining, a computer algorithm segmenting Ki67 and Ki67 tumor cells using digitally fused parallel cytokeratin and Ki67-stained slides, has been introduced. In this study, we compare Ki67 PIs obtained by virtual double staining in 41 breast carcinomas stained using the most commonly used commercially available primary Ab clones and formats on the main stainer platforms. IHC protocols for the concentrated (conc) Ab and platform combinations were optimized for the highest analytical sensitivity and optimal signal-to-noise ratio, whereas ready-to-use (RTU) formats were used, as recommended by the vendor. Significant differences in the mean Ki67 PIs (relativized to the mean core Ki67) were observed not only between the different Ab clones but also the different formats and stainer platforms; Ki67 PIs with SP6 conc stained on the Ventana BenchMark ULTRA platform were on average 11.9 percentage points (pp) higher than the mean core average, whereas with Ab 30.9 RTU on the Ventana platform, they were 10.4 pp higher. Mib1 RTU (Dako Autostainer Link 48) and MM1 RTU (Leica Bond) provided 8.6 and 12.5 pp lower Ki67 PIs, respectively. Mib1 conc and SP6 conc on the Dako Autostainer and Leica Bond provided similar results-close to the overall average. Significant variations in the proportion of tumors with Ki67 high-level expression (Ki67 PI ≥20%) were observed among Ab, format, and stainer platform combinations. The results underline the challenges in the comparison of Ki67 PIs across Abs, formats, and platforms. Researchers and clinicians need to account for these differences when reporting Ki67 PIs. To advance the usefulness of Ki67 PIs in the research and clinical setting, standardization of Ki67 IHC assays is needed.

Bone marrow cellularity is an important measure in diagnostic hematopathology. Currently, the gold standard for bone marrow cellularity estimation is manual inspection of hematoxylin and eosin stained whole slide images (H&E WSI) by hematopathologists. However, these assessments are subjective and subject to interobserver and intraobserver variability. This may be reduced by using a computer-assisted estimate of bone marrow cellularity. The aim of this study was to develop a fully automated algorithm to estimate bone marrow cellularity in H&E WSI stains using bone marrow segmentation. Data consisted of eight bone marrow H&E WSIs extracted from eight subjects. An algorithm was developed to estimate the bone marrow cellularity consisting of biopsy segmentation, tissue classification, and bone marrow segmentation. Segmentations of the red and yellow bone marrow (YBM) were used to estimate the bone marrow cellularity within the WSI H&E stains. The DICE coefficient between automatic tissue segmentations and ground truth segmentations conducted by an experienced hematopathologist were used for validation. Furthermore, the agreement between the automatic and two manual cellularity estimates was assessed using Bland-Altman plots and intraclass correlation coefficients (ICC). The validation of the bone marrow segmentation demonstrated an average DICE of 0.901 and 0.920 for the red and YBM, respectively. A mean cellularity estimate difference of -0.552 and - 7.816 was obtained between the automatic cellularity estimates and two manual cellularity estimates, respectively. An ICC of 0.980 (95%CI: 0.925-0.995, P-value: 5.51 × 10-7 ) was obtained between the automatic and manual cellularity estimates based on manual annotations. The study demonstrated that it was possible to obtain bone marrow cellularity estimates with a good agreement with bone marrow cellularity estimates obtained from an experienced hematopathologist. © 2019 International Society for Advancement of Cytometry.

This paper is the number 5 in a series developed through a partnership between ISIMM and NordiQC for the purpose of reporting research assessing the performance characteristics of immunoassays in an external proficiency-testing program.

Mediastinal pure choriocarcinomas are exceedingly rare representations of germ cell tumours and are associated with a poor prognosis. To date, fewer than 20 cases have been reported. This current report describes an elderly patient who developed a large rapidly growing mediastinal tumour. Unfortunately, the patient expired before a definitive diagnosis could be reached. An autopsy revealed that the histomorphological features of the tumour showed two distinct tumour cell populations (syncytio- and cytotrophoblasts), and the diagnosis of choriocarcinoma was made. Immunohistochemical analysis showed a characteristic staining pattern in agreement with published studies. Here, we report a case of primary mediastinal choriocarcinoma in an elderly male with concurrent metastasizing prostate adenocarcinoma treated with long-term goserelin deposits, which, as we speculate, could have induced the choriocarcinoma.

Functional magnetic resonance imaging (fMRI) is widely used to measure brain function during various cognitive states. However, it remains a challenge to obtain low-rank models of functional networks in fMRI that have interpretable latent features and generalize across groups of subjects, due to significant intersubject variability in the signal structure and noise. Group-level modeling is typically performed using component decompositions such as independent component analysis (ICA), which represent data as a linear combination of latent brain patterns, or using clustering models, where data are assumed to be generated by a set of “prototype” time series. Archetypal analysis (AA) provides a promising alternative, combining the advantages of component-model flexibility with highly interpretable latent “archetypes” (similar to cluster-model prototypes). To date, AA has not been applied to group-level fMRI; a major limitation is that it does not generalize to multi-subject datasets, which may have significant variations in blood oxygenation-level-dependent signal and heteroscedastic noise. We develop multi-subject AA (MS-AA), which accounts for group-level data by assuming that archetypal temporal profiles have a common latent generator across subjects, ensuring that the temporal components are derived from a consistent set of brain regions. In addition, the model accounts for noise heteroscedasticity by modeling subject- and voxel-specific noise variance. This provides a novel approach to group-level modeling and an alternative to preexisting methods that account for inter-subject variability by extracting individual maps as a postprocessing step (e.g., dual-regression ICA), or assuming spatial dependency of maps across subjects (e.g., independent vector analysis). MS-AA shows robust performance when modelling archetypes for a motor task experiment. The procedure extracts a “seed map” across subjects, used to provide brain parcellations with subject-specific temporal profiles. Our approach thus decomposes multisubject fMRI data into distinct interpretable component archetypes that may help to model both consistent group-level measures of fMRI data and individual variability.

Background: Middle ear physiology includes both sound pressure transmission and homeostasis of its static air pressure. Pressure gradients are continuously created by gas exchange over the middle ear mucosa as well as by ambient pressure variations. Gas exchange models require actual values for regional mucosa thickness, blood vessel density, and diffusion distance. Such quantitative data have been scarce and limited to few histological samples from the tympanic cavity (TC) and the antrum. However, a detailed regional description of the morphological differences of the TC and mastoid air cell system (MACS) mucosa has not been available. The aim of the present study was to provide such parameters. Methods: The study included sets of three histological H&E-slides from 15 archived healthy temporal bones. We performed a comparison of the mucosa morphology among the following regions: (1) anterior TC; (2) inferior TC; (3) posterior TC; (4) superior TC; (5) MACS antrum; (6) superior MACS; (7) central MACS; (8) inferior MACS. Results: Regions (1)–(3), situated below the inter-attico-tympanic diaphragm, had the largest proportion of high respiratory epithelium, cilia and loose lamina propria within the mucosa, as well as the thickest mucosa and the largest diffusion distance. Regions (6)–(8), situated above the diaphragm, had the thinnest mucosa, the shortest distance to the blood vessels, together with the largest proportion of flat epithelium and very few cilia. Regions (4)–(5), still supradiaphragmatic, had intermediary values for these parameters, but generally closer to regions (6)–(8). The blood vessel density and the proportion of active mucosa were not significantly different among the regions. Conclusion: Mucosa of regions (1), (2) and (3) represented a predominantly clearance-specific morphology, whereas in regions (4)–(8) it seemed adapted to gas exchange. However, the lack of statistically significant differences in blood vessel density and proportion of active mucosa indicated that all regions could be involved in gas exchange with the highest adaptation in the superior MACS. This pattern divides the middle ear functionally along the inter-attico-tympanic diaphragm rather than the anatomical division into TC and MACS.

Currently, colon cancer diagnosis is based on manual assessment of tissue samples stained with hematoxylin and eosin (H&E). This is a high volume, time consuming, and subjective task which could be aided by automatic cancer detection. We propose an algorithm for automatic cancer detection within WSI H&E stains using a multi class colon tissue classifier based on features extracted from 5 different color representations. Approx. 32000 tissue patches were extracted for the classifier from manual annotations of 9 representative colon tissue types from 74 WSI H&E stains. Colon tissue classifiers based on gray level or color features were trained using leave-one-out forward selection. The best colon tissue classifier was based on color texture features obtaining an average tissue precision-recall (PR) area under the curve (AUC) of 0.886 and a cancer PR-AUC of 0.950 on 20 validation WSI H&E stains.

This paper is number 4 in a series developed through a partnership between ISIMM and Nordic immunohistochemical Quality Control for the purpose of reporting research assessing the performance characteristics of immunoassays in an external proficiency testing program.

This paper is number 3 in a series developed through a partnership between ISIMM and NordiQC for the purpose of reporting research assessing the performance characteristics of immunoassays in an external proficiency testing program.

This paper is number 2 in a series developed through a partnership between ISIMM and NordiQC for the purpose of reporting research assessing the performance characteristics of immunoassays in an external proficiency testing program.

Cluster analysis of functional magnetic resonance imaging (fMRI) data is often performed using gaussian mixture models, but when the time series are standardized such that the data reside on a hypersphere, this modeling assumption is questionable. The consequences of ignoring the underlying spherical manifold are rarely analyzed, in part due to the computational challenges imposed by directional statistics. In this letter, we discuss a Bayesian von Mises–Fisher (vMF) mixture model for data on the unit hypersphere and present an efficient inference procedure based on collapsed Markov chain Monte Carlo sampling. Comparing the vMF and gaussian mixture models on synthetic data, we demonstrate that the vMF model has a slight advantage inferring the true underlying clustering when compared to gaussian-based models on data generated from both a mixture of vMFs and a mixture of gaussians subsequently normalized. Thus, when performing model selection, the two models are not in agreement. Analyzing multisubject whole brain resting-state fMRI data from healthy adult subjects, we find that the vMF mixture model is considerably more reliable than the gaussian mixture model when comparing solutions across models trained on different groups of subjects, and again we find that the two models disagree on the optimal number of components. The analysis indicates that the fMRI data support more than a thousand clusters, and we confirm this is not a result of overfitting by demonstrating better prediction on data from held-out subjects. Our results highlight the utility of using directional statistics to model standardized fMRI data and demonstrate that whole brain segmentation of fMRI data requires a very large number of functional units in order to adequately account for the discernible statistical patterns in the data.

Treatment using immunotherapy against PD-L1 or PD-1 has become one of the hottest topics in Pathology and Oncology. Correct selection of patients eligible for treatment requires optimal immunohistochemical staining protocols. Treatment with pembrolizumab requires diagnostic examination of the patient's tumour using the companion diagnostic Ready-To-Use pharmDx kit from Dako Agilent based on the mAb 22C3 clone on the Autostainer platform. However, not all diagnostic pathology labs have access to this staining platform. This purpose of this study was to develop and validate protocols for PD-L1 detection for all major staining platforms using the concentrated format of 22C3 that would give similar staining result (equal Tumour Proportion Scores) to the pharmDx kit.

Modern functional and diffusion magnetic resonance imaging (fMRI and dMRI) provide data from which macro-scale networks of functional and structural whole brain connectivity can be estimated. Although networks derived from these two modalities describe different properties of the human brain, they emerge from the same underlying brain organization, and functional communication is presumably mediated by structural connections. In this paper, we assess the structure-function relationship by evaluating how well functional connectivity can be predicted from structural graphs. Using high-resolution whole brain networks generated with varying density, we contrast the performance of several non-parametric link predictors that measure structural communication flow. While functional connectivity is not well predicted directly by structural connections, we show that superior predictions can be achieved by taking indirect structural pathways into account. In particular, we find that the length of the shortest structural path between brain regions is a good predictor of functional connectivity in sparse networks (density less than one percent), and that this improvement comes from integrating indirect pathways comprising up to three steps. Our results support the existence of important indirect relationships between structure and function, extending beyond the immediate direct structural connections that are typically investigated.

Currently, diagnosis of colon cancer is based on manual examination of histopathological images by a pathologist. This can be time consuming and interpretation of the images is subject to inter- and intra-observer variability. This may be improved by introducing a computer-aided diagnosis (CAD) system for automatic detection of cancer tissue within whole slide hematoxylin and eosin (HE) stains. Cancer disrupts the normal control mechanisms of cell proliferation and differentiation, affecting the structure and appearance of the cells. Therefore, extracting features from segmented cell nuclei structures may provide useful information to detect cancer tissue. A framework for automatic classification of regions of interest (ROI) containing either benign or cancerous colon tissue extracted from whole slide HE stained images using cell nuclei features was proposed. A total of 1,596 ROI's were extracted from 87 whole slide HE stains (44 benign and 43 cancer). A cell nuclei segmentation algorithm consisting of color deconvolution, k-means clustering, local adaptive thresholding, and cell separation was performed within the ROI's to extract cell nuclei features. From the segmented cell nuclei structures a total of 750 texture and intensity-based features were extracted for classification of the ROI's. The nine most discriminative cell nuclei features were used in a random forest classifier to determine if the ROI's contained benign or cancer tissue. The ROI classification obtained an area under the curve (AUC) of 0.96, sensitivity of 0.88, specificity of 0.92, and accuracy of 0.91 using an optimized threshold. The developed framework showed promising results in using cell nuclei features to classify ROIs into containing benign or cancer tissue in HE stained tissue samples. © 2017 International Society for Advancement of Cytometry.

Increased consumption of high-caloric carbohydrates contributes substantially to endemic non-alcoholic fatty liver disease in humans, covering a histological spectrum from fatty liver to steatohepatitis. Hypercaloric intake and lipogenetic effects of fructose and endotoxin-driven activation of liver macrophages are suggested to be essential to disease progression. In the present study, we show that a low dose of an anti-CD163-IgG-dexamethasone conjugate targeting the hemoglobin scavenger receptor CD163 in Kupffer cells and other M2-type macrophages has a profound effect on liver inflammatory changes in rats on a high-fructose diet. The diet induced severe non-alcoholic steatohepatitis (NASH)-like changes within a few weeks but the antibody-drug conjugate strongly reduced inflammation, hepatocyte ballooning, fibrosis, and glycogen deposition. Non-conjugated dexamethasone or dexamethasone conjugated to a control IgG did not have this effect but instead exacerbated liver lipid accumulation. The low-dose anti-CD163-IgG-dexamethasone conjugate displayed no apparent systemic side effects. In conclusion, macrophage targeting by antibody-directed anti-inflammatory low-dose glucocorticoid therapy seems to be a promising approach for safe treatment of fructose-induced liver inflammation.

Background: Numerous studies on seasonality of birth and schizophrenia risk have been published but it is uncertain whether, among those with schizophrenia, refractory illness exhibits any predilection for birth month. We hypothesized and examined whether a season of birth effect was present in patients with schizophrenia with a history of clozapine treatment. Method: Using record linkage with Danish registers, we examined patients with schizophrenia born between 1950 and 1970, and between 1995 and 2009 and Cox regression analysis was used to examine season of birth in relation to history of clozapine treatment. Results: In a study population corresponding to 60,062 person-years from 5328 individuals with schizophrenia of which 1223 (23%) received at least one clozapine prescription, birth in the autumn (September – November) was associated with clozapine treatment (HR 1.24; 95% CI 1.07 – 1.46) when compared with birth in the spring (March – May). Conclusion: Although replication studies are needed, this is the fi rst evidence from a nationwide study suggesting a possible seasonassociated risk of clozapine treatment in schizophrenia. The reasons for this relationship remain to be further investigated but might be partially explained by early exposures such as winter flu season and low vitamin D levels. Background: Numerous studies on seasonality of birth and schizophrenia risk have been published but it is uncertain whether, among those with schizophrenia, refractory illness exhibits any predilection for birth month. We hypothesized and examined whether a season of birth effect was present in patients with schizophrenia with a history of clozapine treatment. Method: Using record linkage with Danish registers, we examined patients with schizophrenia born between 1950 and 1970, and between 1995 and 2009 and Cox regression analysis was used to examine season of birth in relation to history of clozapine treatment. Results: In a study population corresponding to 60,062 person-years from 5328 individuals with schizophrenia of which 1223 (23%) received at least one clozapine prescription, birth in the autumn (September – November) was associated with clozapine treatment (HR 1.24; 95% CI 1.07 – 1.46) when compared with birth in the spring (March – May). Conclusion: Although replication studies are needed, this is the fi rst evidence from a nationwide study suggesting a possible seasonassociated risk of clozapine treatment in schizophrenia. The reasons for this relationship remain to be further investigated but might be partially explained by early exposures such as winter flu season and low vitamin D levels.

Manual estimation of Ki67 Proliferation Index (PI) in breast carcinoma classification is labor intensive and prone to intra- and interobserver variation. Standard Digital Image Analysis (DIA) has limitations due to issues with tumor cell identification. Recently, a computer algorithm, DIA based on Virtual Double Staining (VDS), segmenting Ki67-positive and -negative tumor cells using digitally fused parallel cytokeratin (CK) and Ki67-stained slides has been introduced. In this study, we compare VDS with manual stereological counting of Ki67-positive and -negative cells and examine the impact of the physical distance of the parallel slides on the alignment of slides. TMAs, containing 140 cores of consecutively obtained breast carcinomas, were stained for CK and Ki67 using optimized staining protocols. By means of stereological principles, Ki67-positive and -negative cell profiles were counted in sampled areas and used for the estimation of PIs of the whole tissue core. The VDS principle was applied to both the same sampled areas and the whole tissue core. Additionally, five neighboring slides were stained for CK in order to examine the alignment algorithm. Correlation between manual counting and VDS in both sampled areas and whole core was almost perfect (correlation coefficients above 0.97). Bland-Altman plots did not reveal any skewness in any data ranges. There was a good agreement in alignment (>85 %) in neighboring slides, whereas agreement decreased in non-neighboring slides. VDS gave similar results compared with manual counting using stereological principles. Introduction of this method in clinical and research practice may improve accuracy and reproducibility of Ki67 PI.

Dynamic functional connectivity (FC) has in recent years become a topic of interest in the neuroimaging community. Several models and methods exist for both functional magnetic resonance imaging (fMRI) and electroencephalography (EEG), and the results point towards the conclusion that FC exhibits dynamic changes. The existing approaches modeling dynamic connectivity have primarily been based on time-windowing the data and k-means clustering. We propose a non-parametric generative model for dynamic FC in fMRI that does not rely on specifying window lengths and number of dynamic states. Rooted in Bayesian statistical modeling we use the predictive likelihood to investigate if the model can discriminate between a motor task and rest both within and across subjects. We further investigate what drives dynamic states using the model on the entire data collated across subjects and task/rest. We find that the number of states extracted are driven by subject variability and preprocessing differences while the individual states are almost purely defined by either task or rest. This questions how we in general interpret dynamic FC and points to the need for more research on what drives dynamic FC., Comment: 8 pages, 1 figure. Presented at the Machine Learning and Interpretation in Neuroimaging Workshop (MLINI-2015), 2015 (arXiv:1605.04435)

Functional Magnetic Resonance Imaging has become a central measuring modality to quantify functional activiation of the brain in both task and rest. Most analysis used to quantify functional activation requires supervised approaches as employed in statistical parametric mapping (SPM) to extract maps of task induced functional activations. This requires strong knowledge and assumptions on the BOLD response as a function of activitation while smoothing in general enhances the statistical power but at the cost of spatial resolution. We propose a fully unsupervised approach for the extraction of task activated functional units in multi-subject fMRI data that exploits that regions of task activation are consistent across subjects and can be more reliably inferred than regions that are not activated. We develop a non-parametric Gaussian mixture model that apriori assumes activations are smooth using a Gaussian Process prior while assuming the segmented functional maps are the same across subjects but having individual time-courses and noise variances. To improve inference we propose an enhanced split-merge procedure. We find that our approach well extracts the induced activity of a finger tapping fMRI paradigm with maps that well corresponds to a supervised group SPM analysis. We further find interesting regions that are not activated time locked to the paradigm. Demonstrating that we in a fully unsupervised manner are able to extract the task-induced activations forms a promising framework for the analysis of task fMRI and resting-state data in general where strong knowledge of how the task induces a BOLD response is missing.

BACKGROUND: The etiology of schizophrenia remains largely unknown but alterations in the immune system may be involved. In addition to the psychiatric symptoms, schizophrenia is also associated with up to 20 years reduction in life span. Soluble urokinase-type plasminogen activator receptor (suPAR) is a protein that can be measured in blood samples and reflects the levels of inflammatory activity. It has been associated with mortality and the development of type 2 diabetes and cardiovascular disease.METHODS: suPAR levels in patients with schizophrenia were compared to healthy controls from the Danish Blood Donor Study. SuPAR levels were dichotomized at >4.0 ng/ml, which is considered the threshold for low grade inflammation. A multiple logistic regression model was used and adjusted for age, sex, and current smoking.RESULTS: In total we included 1009 subjects, 105 cases with schizophrenia (10.4%) and 904 controls (89.6%). The mean suPAR values were 4.01 ng/ml (SD = 1.43) for the cases vs 1.91 ng/ml (SD = 1.35) for the controls (P < .001). Multiple logistic regression with odds ratio (OR) for suPAR levels >4.0 ng/ml yielded: schizophrenia, OR: 46.15 95% CI 22.69-93.87, P < .001; age, OR: 1.02 95% CI 0.99-1.02, P = .15; male sex, OR: 0.70 95% CI 0.35-1.36, P = .29; and current smoking, OR: 3.51 95% CI 1.78-6.94, P < .001.CONCLUSIONS: Patients with schizophrenia had significantly higher suPAR levels than healthy controls. Further studies are warranted to clarify if elevated suPAR levels are involved in the pathophysiology of schizophrenia and/or the increased mortality found in patients with schizophrenia.

Immunohistochemical detection of CD15 is important in the diagnosis of Hodgkin lymphoma and may play a role in the classification of renal cell tumors (RCTs). In the NordiQC external quality assessment scheme, 4 CD15 tests, each with 71 to 121 participating laboratories, showed that 24% to 50% of the stains were insufficient. This was mainly because of very low primary antibody (Ab) concentration and insufficient heat-induced epitope retrieval, whereas the Ab clone performance seemed of little importance. The purpose of this study was to evaluate the performance of the most commonly used CD15 Abs on the basis of vendor-recommended and in-house optimized protocols. Multitissue blocks with 199 specimens including various malignant lymphomas, RCTs, and normal tissues were stained with 3 different concentrated (conc) CD15 Ab clones Carb-3, MMA, and BY87 according to predetermined in-house optimized protocols on 2 automated immunostaining platforms. Carb-3 and MMA were also applied in ready-to-use (RTU) formats utilized according to vendor protocols. Extension and intensity of stains was determined using the H-score method. Clone Carb-3-conc gave with an in-house optimized protocol the highest H-scores in Hodgkin lymphoma, RCTs, and normal kidney tissue. Clones Carb-3-RTU and MMA-conc gave slightly lower scores, whereas clones MMA-RTU and BY87-conc gave the lowest scores and a large proportion of false-negative reactions. For all concentrated Abs, in-house optimized protocols resulted in increased sensitivity and improved overall staining results compared with vendor-recommended protocols. The importance of Ab selection and protocol optimization in immunohistochemical laboratories is emphasized.

Despite its unsurpassed efficacy in treatment-resistant schizophrenia, clozapine remains underutilized. Trends in the prescription of clozapine in patients with ICD-10 F20.x schizophrenia were assessed using data from Danish national registers. Three substudies were carried out: (i) an assessment of differences in national prescription patterns between 1996 and 2007 using a cross-sectional design; (ii) a comparison of time from first schizophrenia diagnosis to first prescription of clozapine in a five-year cohort study, using the Cox regression model, of two patient groups who were first diagnosed in 1996 and in 2003; (iii) an assessment of differences in the general psychiatric hospitals' use of clozapine in 2009. The results are as follows: (i) The percentage of schizophrenia patients receiving clozapine rose from 9.0% in 1996 to 10.1% in 2007 (p

Clozapine remains the drug of choice for treatment resistant schizophrenia, but is associated with potentially life threatening side effects, including agranulocytosis and myocarditis. Immunological mechanisms may be involved in the development of these side effects or in the unique antipsychotic efficacy in subgroups of schizophrenia patients. This systematic review presents the immunomodulatory effects of clozapine from human in vitro and in vivo studies and relates these findings to the developments of adverse and therapeutic effects of clozapine. Several studies confirm the immunomodulatory actions of clozapine, but only few studies investigated their relationship to the unique adverse and therapeutic effects of clozapine. During the first month of clozapine treatment, up to 50% of patients develop fever and flu like symptoms, which is seemingly driven by increased cytokines. Within the same time period, the risk of side-effects with a suspected immunological mechanism peaks. Patients developing fever during the first weeks of treatment should have a thorough physical examination, and measurements of white blood cell count, absolute neutrophil count, ECG, C-reactive protein, creatinine kinase, and troponin to exclude infection, agranulocytosis, myocarditis and neuroleptic malignant syndrome. To what degree the unique antipsychotic efficacy of clozapine in subgroups of schizophrenia patients is related to its immunomodulatory effects has not been studied. Research relating the immunomodulatory actions of clozapine and its early markers to clinically relevant adverse and therapeutic outcomes is hoped to provide new leads for the understanding of the pathophysiology of schizophrenia and aid the development of novel treatment targets.

Background Tacrolimus exerts its immunosuppressive effect through inhibition of the intracellular enzyme calcineurin phosphatase (CaN). In this study, we set-up a validated real-time PCR method to measure the gene expression of the two major isoforms of the catalytic subunit of CaN in T-lymphocytes. Methods 20 stable kidney-transplant recipients, 10 early kidney-transplant recipients and 10 healthy non-medicated subjects had blood drawn and T-lymphocytes were isolated using E-rosette gradient centrifugation method. The cell counts were analyzed by DNA quantification using Hoeschst 33285. Gene expressions were analyzed using real-time PCR for CaN Aα, CaN Aβ and the reference genes CD3E and PPIB. Results The real-time PCR method was found to be with high efficiencies and low intra- and inter-assay variabilities. No statistically significant differences were found in the gene expression levels of the two reference genes among the three groups. The two major isoforms of CaN A were expressed in equal amounts in the T-lymphocytes. Conclusion We found no significant difference in the reference genes between the three groups, but looking at the data there was a trend towards an up-regulation of CD3E. PPIB appears to be the more stable of the two reference genes tested in our study.

Quantitative polymerase chain reaction (Q-PCR) studies of urine sediments have demonstrated an increased expression of cytotoxin genes during episodes of acute rejection of renal allografts. To compensate for differences in initial sample size and cDNA preparation, standard Q-PCR experiments involve normalization to a reference gene. Although stable expression of reference genes is a prerequisite for any Q-PCR analysis, commonly used reference genes have demonstrated a varying expression across tissues and various stimuli. In this study, cellular expression of several reference genes was investigated in a mixed lymphocyte reaction as a model of gene expression during alloreactive T-lymphocyte activation and acute rejection. Gene expression was quantified using Q-PCR, normalized to cell counts obtained by DNA quantification and corrected for cell polyploidy using flow cytometry. Examined reference genes were 18S rRNA, beta-actin (ACTB), hydroxymethylbilane synthase (HMBS), hypoxanthine phosphoribosyltransferase (HPRT1) and peptidylprolyle isomerase B (PPIB). This study also examined two novel T-lymphocyte-specific reference genes: CD3E and CD8B. HMBS and HPRT were 18.8- and 7.4-fold upregulated, respectively, ACTB was 5.3-fold upregulated, PPIB was 3.2-fold upregulated while 18S rRNA remained stably expressed. The T-lymphocyte-specific reference gene CD3E remained stable while CD8B was upregulated 2.3-fold. In conclusion, several commonly used reference genes were actively regulated during alloreactive T-lymphocyte activation. Additionally, we introduce two stable T-lymphocyte-specific reference genes that might be useful in a Q-PCR analysis of T-lymphocyte-specific cytotoxin genes in urine sediments, as they overcome the contribution of reference gene mRNA from cells irrelevant for diagnosis.